Why Use Docker In Machine Learning? We Explain With Use Cases

Docker is everywhere in the software industry today. Mostly popular as a DevOps tool, Docker has stolen the hearts of many developers, system administrators and engineers, among others. "Docker is a tool that helps users to exploit operating-system-level virtualisation to develop and deliver software in packages called containers." This technical definition may sound complicated, but all you need to know is that Docker is a complete environment where you can build and deploy software. It is just like your Linux machine, except that it is very lightweight, fast and has nothing except what you need for your project or software to run without a glitch. One of the best things about Docker is that you can move it across platforms and still run without installing a single dependency -- because all you need is a Docker Engine.